On the convergence of adaptive gPC for non-linear random difference equations: Theoretical analysis and some practical recommendations
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http://dx.doi.org/10.22436/jnsa.011.09.06 |
Metadades
Títol
On the convergence of adaptive gPC for non-linear random difference equations: Theoretical analysis and some practical recommendationsData de publicació
2018-06-19Editor
International Scientific Research PublicationsISSN
2008-1898; 2008-1901Cita bibliogràfica
Calatayud, J., Cortés, J. C., & Jornet, M. (2018). On the convergence of adaptive gPC for non-linear random difference equations: Theoretical analysis and some practical recommendations. Journal of Nonlinear Sciences & Applications (JNSA), 11(9).Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://www.isr-publications.com/jnsa/articles-7147-on-the-convergence-of-adapti ...Versió
info:eu-repo/semantics/publishedVersionParaules clau / Matèries
Resum
In this paper, the application of adaptive generalized polynomial chaos (gPC) to quantify the uncertainty for non-linear
random difference equations is analyzed. It is proved in detail that, under certain assumptions, ... [+]
In this paper, the application of adaptive generalized polynomial chaos (gPC) to quantify the uncertainty for non-linear
random difference equations is analyzed. It is proved in detail that, under certain assumptions, the stochastic Galerkin projection
technique converges algebraically in mean square to the solution process of the random recursive equation. The effect of the
numerical errors on the convergence is also studied. A full numerical experiment illustrates our theoretical findings and gives
useful insights to reduce the accumulation of numerical errors in practice. [-]
Publicat a
Journal of Nonlinear Sciences and Applications (JNSA), Vol. 11 (2018)Entitat finançadora
Ministerio de Economía y Competitividad | Universitat Politècnica de València
Codi del projecte o subvenció
MTM2017–89664–P
Títol del projecte o subvenció
Programa de Ayudas de Investigación y Desarrollo (PAID)
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